Understanding epigenetic changes in aging stem cells--a computational model approach

Single-cell transcriptomics of human iPSC differentiation dynamics reveal a core molecular network of Parkinson's disease

Parkinson's disease (PD) is the second-most prevalent neurodegenerative disorder, characterized by the loss of dopaminergic neurons (mDA) in the midbrain. The underlying mechanisms are only partly understood and there is no treatment to reverse PD progression. Here, we investigated the disease mechanism using mDA neurons differentiated from human induced pluripotent stem cells (hiPSCs) carrying the ILE368ASN mutation within the PINK1 gene, which is strongly associated with PD. Single-cell RNA sequencing (RNAseq) and gene expression analysis of a PINK1-ILE368ASN and a control cell line identified genes differentially expressed during mDA neuron differentiation. Network analysis revealed that these genes form a core network, members of which interact with all known 19 protein-coding Parkinson's disease-associated genes. This core network encompasses key PD-associated pathways, including ubiquitination, mitochondrial function, protein processing, RNA metabolism, and vesicular transport. Proteomics analysis showed a consistent alteration in proteins of dopamine metabolism, indicating a defect of dopaminergic metabolism in PINK1-ILE368ASN neurons. Our findings suggest the existence of a network onto which pathways associated with PD pathology converge, and offers an inclusive interpretation of the phenotypic heterogeneity of PD.

Why stem/progenitor cells lose their regenerative potential

Nowadays, it is clear that adult stem cells, also called as tissue stem cells, play a central role to repair and maintain the tissue in which they reside by their self-renewal ability and capacity of differentiating into distinct and specialized cells. As stem cells age, their renewal ability declines and their capacity to maintain organ homeostasis and regeneration is impaired. From a molecular perspective, these changes in stem cells properties can be due to several types of cell intrinsic injury and DNA aberrant alteration (i.e epigenomic profile) as well as changes in the tissue microenviroment, both into the niche and by systemic circulating factors. Strikingly, it has been suggested that aging-induced deterioration of stem cell functions may play a key role in the pathophysiology of the various aging-associated disorders. Therefore, understanding how resident stem cell age and affects near and distant tissues is fundamental. Here, we examine the current knowledge about aging mechanisms in several kinds of adult stem cells under physiological and pathological conditions and the principal aging-related changes in number, function and phenotype that determine the loss of tissue renewal properties. Furthermore, we examine the possible cell rejuvenation strategies. Stem cell rejuvenation may reverse the aging phenotype and the discovery of effective methods for inducing and differentiating pluripotent stem cells for cell replacement therapies could open up new possibilities for treating age-related diseases.

Modeling aging and its impact on cellular function and organismal behavior

Aging is a complex phenomenon of functional decay in a biological organism. Although the effects of aging are readily recognizable in a wide range of organisms, the cause(s) of aging are ill defined and poorly understood. Experimental methods on model organisms have driven significant insight into aging as a process, but have not provided a complete model of aging. Computational biology offers a unique opportunity to resolve this gap in our knowledge by generating extensive and testable models that can help us understand the fundamental nature of aging, identify the presence and characteristics of unaccounted aging factor(s), demonstrate the mechanics of particular factor(s) in driving aging, and understand the secondary effects of aging on biological function. In this review, we will address each of the above roles for computational biology in aging research. Concurrently, we will explore the different applications of computational biology to aging in single-celled versus multicellular organisms. Given the long history of computational biogerontological research on lower eukaryotes, we emphasize the key future goals of gradually integrating prior models into a holistic map of aging and translating successful models to higher-complexity organisms.

Brain aging and garbage cleaning : Modelling the role of sleep, glymphatic system, and microglia senescence in the propagation of inflammaging

Brain aging is a complex process involving many functions of our body and described by the interplay of a sleep pattern and changes in the metabolic waste concentration regulated by the microglial function and the glymphatic system. We review the existing modelling approaches to this topic and derive a novel mathematical model to describe the crosstalk between these components within the conceptual framework of inflammaging. Analysis of the model gives insight into the dynamics of garbage concentration and linked microglial senescence process resulting from a normal or disrupted sleep pattern, hence, explaining an underlying mechanism behind healthy or unhealthy brain aging. The model incorporates accumulation and elimination of garbage, induction of glial activation by garbage, and glial senescence by over-activation, as well as the production of pro-inflammatory molecules by their senescence-associated secretory phenotype (SASP). Assuming that insufficient sleep leads to the increase of garbage concentration and promotes senescence, the model predicts that if the accumulation of senescent glia overcomes an inflammaging threshold, further progression of senescence becomes unstoppable even if a normal sleep pattern is restored. Inverting this process by "rejuvenating the brain" is only possible via a reset of concentration of senescent glia below this threshold. Our model approach enables analysis of space-time dynamics of senescence, and in this way, we show that heterogeneous patterns of inflammation will accelerate the propagation of senescence profile through a network, confirming a negative effect of heterogeneity.

Fighting Against Promoter DNA Hyper-Methylation: Protective Histone Modification Profiles of Stress-Resistant Intestinal Stem Cells

Aberrant DNA methylation in stem cells is a hallmark of aging and tumor development. Recently, we have suggested that promoter DNA hyper-methylation originates in DNA repair and that even successful DNA repair might confer this kind of epigenetic long-term change. Here, we ask for interrelations between promoter DNA methylation and histone modification changes observed in the intestine weeks after irradiation and/or following Msh2 loss. We focus on H3K4me3 recruitment to the promoter of H3K27me3 target genes. By RNA- and histone ChIP-sequencing, we demonstrate that this recruitment occurs without changes of the average gene transcription and does not involve H3K9me3. Applying a mathematical model of epigenetic regulation of transcription, we show that the recruitment can be explained by stronger DNA binding of H3K4me3 and H3K27me3 histone methyl-transferases as a consequence of lower DNA methylation. This scenario implicates stable transcription despite of H3K4me3 recruitment, in agreement with our RNA-seq data. Following several kinds of stress, including moderate irradiation, stress-sensitive intestinal stem cell (ISCs) are known to become replaced by more resistant populations. Our simulation results suggest that the stress-resistant ISCs are largely protected against promoter hyper-methylation of H3K27me3 target genes.

DNA methylation aging clocks: challenges and recommendations

Epigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.

A multi-tissue full lifespan epigenetic clock for mice

Human DNA-methylation data have been used to develop highly accurate biomarkers of aging ("epigenetic clocks"). Recent studies demonstrate that similar epigenetic clocks for mice (Mus Musculus) can be slowed by gold standard anti-aging interventions such as calorie restriction and growth hormone receptor knock-outs. Using DNA methylation data from previous publications with data collected in house for a total 1189 samples spanning 193,651 CpG sites, we developed 4 novel epigenetic clocks by choosing different regression models (elastic net- versus ridge regression) and by considering different sets of CpGs (all CpGs vs highly conserved CpGs). We demonstrate that accurate age estimators can be built on the basis of highly conserved CpGs. However, the most accurate clock results from applying elastic net regression to all CpGs. While the anti-aging effect of calorie restriction could be detected with all types of epigenetic clocks, only ridge regression based clocks replicated the finding of slow epigenetic aging effects in dwarf mice. Overall, this study demonstrates that there are trade-offs when it comes to epigenetic clocks in mice. Highly accurate clocks might not be optimal for detecting the beneficial effects of anti-aging interventions.

Computational modelling folate metabolism and DNA methylation: implications for understanding health and ageing

Dietary folates have a key role to play in health, as deficiencies in the intake of these B vitamins have been implicated in a wide variety of clinical conditions. The reason for this is folates function as single carbon donors in the synthesis of methionine and nucleotides. Moreover, folates have a vital role to play in the epigenetics of mammalian cells by supplying methyl groups for DNA methylation reactions. Intriguingly, a growing body of experimental evidence suggests that DNA methylation status could be a central modulator of the ageing process. This has important health implications because the methylation status of the human genome could be used to infer age-related disease risk. Thus, it is imperative we further our understanding of the processes which underpin DNA methylation and how these intersect with folate metabolism and ageing. The biochemical and molecular mechanisms, which underpin these processes, are complex. However, computational modelling offers an ideal framework for handling this complexity. A number of computational models have been assembled over the years, but to date, no model has represented the full scope of the interaction between the folate cycle and the reactions, which governs the DNA methylation cycle. In this review, we will discuss several of the models, which have been developed to represent these systems. In addition, we will present a rationale for developing a combined model of folate metabolism and the DNA methylation cycle.

Recent Advances in the Systems Biology of Aging

SIGNIFICANCE

Reductionist studies have contributed greatly to our understanding of the basic biology of aging in recent years but we still do not understand fundamental mechanisms for many identified drugs and pathways. Use of systems approaches will help us move forward in our understanding of aging. Recent Advances: Recent work described here has illustrated the power of systems biology to inform our understanding of aging through the study of (i) diet restriction, (ii) neurodegenerative disease, and (iii) biomarkers of aging.

CRITICAL ISSUES

Although we do not understand all of the individual genes and pathways that affect aging, as we continue to uncover more of them, we have now also begun to synthesize existing data using systems-level approaches, often to great effect. The three examples noted here all benefit from computational approaches that were unknown a few years ago, and from biological insights gleaned from multiple model systems, from aging laboratories as well as many other areas of biology.

FUTURE DIRECTIONS

Many new technologies, such as single-cell sequencing, advances in epigenetics beyond the methylome (specifically, assay for transposase-accessible chromatin with high throughput sequencing ), and multiomic network studies, will increase the reach of systems biologists. This suggests that approaches similar to those described here will continue to lead to striking findings, and to interventions that may allow us to delay some of the many age-associated diseases in humans; perhaps sooner that we expect. Antioxid. Redox Signal. 29, 973-984.

Extracellular Vesicles, Ageing, and Therapeutic Interventions

A more comprehensive understanding of the human ageing process is required to help mitigate the increasing burden of age-related morbidities in a rapidly growing global demographic of elderly individuals. One exciting novel strategy that has emerged to intervene involves the use of extracellular vesicles to engender tissue regeneration. Specifically, this employs their molecular payloads to confer changes in the epigenetic landscape of ageing cells and ameliorate the loss of functional capacity. Understanding the biology of extracellular vesicles and the specific roles they play during normative ageing will allow for the development of novel cell-free therapeutic interventions. Hence, the purpose of this review is to summarise the current understanding of the mechanisms that drive ageing, critically explore how extracellular vesicles affect ageing processes and discuss their therapeutic potential to mitigate the effects of age-associated morbidities and improve the human health span.

Linking DNA Damage and Age-Related Promoter DNA Hyper-Methylation in the Intestine

Aberrant DNA methylation in stem cells is a hallmark of aging and tumor development. Here, we explore whether and how DNA damage repair might impact on these time-dependent changes, in particular in proliferative intestinal stem cells. We introduce a 3D multiscale computer model of intestinal crypts enabling simulation of aberrant DNA and histone methylation of gene promoters during aging. We assume histone state-dependent activity of de novo DNA methyltransferases (DNMTs) and methylation-dependent binding of maintenance DNMTs to CpGs. We simulate aging with and without repeated DNA repair. Motivated by recent findings on the histone demethylase KDM2b, we consider that DNA repair is associated with chromatin opening and improved recruitment of de novo DNMTs. Our results suggest that methylation-dependent binding of maintenance DNMTs to CpGs, establishing bistable DNA methylation states, is a prerequisite to promoter hyper-methylation following DNA repair. With this, the transient increase in de novo DNMT activity during repair can induce switches from low to high methylation states. These states remain stable after repair, leading to an epigenetic drift. The switches are most frequent in genes with H3K27me3 modified promoters. Our model provides a mechanistic explanation on how even successful DNA repair might confer long term changes of the epigenome.

Systems Biology in Aging Research

Systems biology is an approach to collect high-dimensional data and analyze in an integrated manner. As aging is a complicated physiological functional decline in biological system, the methods in systems biology could be utilized in aging studies. Here we reviewed recent advances in systems biology in aging research and divide them into two major parts. One is the data resource, which includes omics data from DNA, RNA, proteins, epigenetic changes, metabolisms, and recently single-cell-level variations. The other is the data analysis methods consisting of network and modeling approaches. With all the data and the tools to analyze them, we could further promote our understanding of the systematic aging.

An epigenetic aging clock for dogs and wolves

Several articles describe highly accurate age estimation methods based on human DNA-methylation data. It is not yet known whether similar epigenetic aging clocks can be developed based on blood methylation data from canids. Using Reduced Representation Bisulfite Sequencing, we assessed blood DNA-methylation data from 46 domesticated dogs (Canis familiaris) and 62 wild gray wolves (C. lupus). By regressing chronological dog age on the resulting CpGs, we defined highly accurate multivariate age estimators for dogs (based on 41 CpGs), wolves (67 CpGs), and both combined (115 CpGs). Age related DNA methylation changes in canids implicate similar gene ontology categories as those observed in humans suggesting an evolutionarily conserved mechanism underlying age-related DNA methylation in mammals.

Targeting DNA hypermethylation: Computational modeling of DNA demethylation treatment of acute myeloid leukemia

In acute myeloid leukemia (AML) DNA hypermethylation of gene promoters is frequently observed and often correlates with a block of differentiation. Treatment of AML patients with DNA methyltransferase inhibitors results in global hypomethylation of genes and, thereby, can lead to a reactivation of the differentiation capability. Unfortunately, after termination of treatment both hypermethylation and differentiation block return in most cases. Here, we apply, for the first time, a computational model of epigenetic regulation of transcription to: i) provide a mechanistic understanding of the DNA (de-) methylation process in AML and; ii) improve DNA demethylation treatment strategies. By in silico simulation, we analyze promoter hypermethylation scenarios referring to DNMT dysfunction, decreased H3K4me3 and increased H3K27me3 modification activity, and accelerated cell proliferation. We quantify differences between these scenarios with respect to gene repression and activation. Moreover, we compare the scenarios regarding their response to DNMT inhibitor treatment alone and in combination with inhibitors of H3K27me3 histone methyltransferases and of H3K4me3 histone demethylases. We find that the different hypermethylation scenarios respond specifically to therapy, suggesting that failure of remission originates in patient-specific deregulation. We observe that inappropriate demethylation therapy can result even in enforced deregulation. As an example, our results suggest that application of high DNMT inhibitor concentration can induce unwanted global gene activation if hypermethylation originates in increased H3K27me3 modification. Our results underline the importance of a personalized therapy requiring knowledge about the patient-specific mechanism of epigenetic deregulation.

The Regulatory Capacity of Bivalent Genes-A Theoretical Approach

Bivalent genes are frequently associated with developmental and lineage specification processes. Resolving their bivalency enables fast changes in their expression, which potentially can trigger cell fate decisions. Here, we provide a theoretical model of bivalency that allows for predictions on the occurrence, stability and regulatory capacity of this prominent modification state. We suggest that bivalency enables balanced gene expression heterogeneity that constitutes a prerequisite of robust lineage priming in somatic stem cells. Moreover, we demonstrate that interactions between the histone and DNA methylation machineries together with the proliferation activity control the stability of the bivalent state and can turn it into an unmodified state. We suggest that deregulation of these interactions underlies cell transformation processes as associated with acute myeloid leukemia (AML) and provide a model of AML blast formation following deregulation of the Ten-eleven Translocation (TET) pathway.

Modelling the molecular mechanisms of aging

The aging process is driven at the cellular level by random molecular damage that slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the aging process. The complexity of the aging process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards and discusses many specific examples of models that have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field.

Different in vivo and in vitro transformation of intestinal stem cells in mismatch repair deficiency

Mutations in mismatch repair (MMR) genes result in microsatellite instability (MSI) and early onset of colorectal cancer. To get mechanistic insights into the time scale, sequence and frequency of intestinal stem cell (ISC) transformation, we quantified MSI and growth characteristics of organoids of Msh2-deficient and control mice from birth until tumor formation and related them to tissue gene expression. Although in Msh2-deficient organoids MSI continuously increased from birth, growth characteristics remained stable at first. Months before tumor onset, normal Msh2-deficient tissue contained tumor precursor cells forming organoids with higher MSI, cystic growth and growth rates resembling temporarily those of tumor organoids. Consistently, Msh2-deficient tissue exhibited a tumor-like gene signature. Normal Msh2-deficient organoids showed increased inheritable transient cyst-like growth, which became independent of R-spondin. ISC transformation proceeded faster in vitro than in vivo independent of the underlying genotype but more under MMR deficiency. Transient cyst-like growth but not MSI was suppressed by aspirin. In summary, as highlighted by organoids, molecular alterations continuously proceeded long before tumor onset in MMR-deficient intestine, thus increasing its susceptibility for ISC transformation.

Bistable Epigenetic States Explain Age-Dependent Decline in Mesenchymal Stem Cell Heterogeneity

The molecular mechanisms by which heterogeneity, a major characteristic of stem cells, is achieved are yet unclear. We here study the expression of the membrane stem cell antigen-1 (Sca-1) in mouse bone marrow mesenchymal stem cell (MSC) clones. We show that subpopulations with varying Sca-1 expression profiles regenerate the Sca-1 profile of the mother population within a few days. However, after extensive replication in vitro, the expression profiles shift to lower values and the regeneration time increases. Study of the promoter of Ly6a unravels that the expression level of Sca-1 is related to the promoter occupancy by the activating histone mark H3K4me3. We demonstrate that these findings can be consistently explained by a computational model that considers positive feedback between promoter H3K4me3 modification and gene transcription. This feedback implicates bistable epigenetic states which the cells occupy with an age-dependent frequency due to persistent histone (de-)modification. Our results provide evidence that MSC heterogeneity, and presumably that of other stem cells, is associated with bistable epigenetic states and suggest that MSCs are subject to permanent state fluctuations. Stem Cells 2017;35:694-704.

A Computational Model of Cellular Engraftment on Lung Scaffolds

The possibility that stem cells might be used to regenerate tissue is now being investigated for a variety of organs, but these investigations are still essentially exploratory and have few predictive tools available to guide experimentation. We propose, in this study, that the field of lung tissue regeneration might be better served by predictive tools that treat stem cells as agents that obey certain rules of behavior governed by both their phenotype and their environment. Sufficient knowledge of these rules of behavior would then, in principle, allow lung tissue development to be simulated computationally. Toward this end, we developed a simple agent-based computational model to simulate geographic patterns of cells seeded onto a lung scaffold. Comparison of the simulated patterns to those observed experimentally supports the hypothesis that mesenchymal stem cells proliferate preferentially toward the scaffold boundary, whereas alveolar epithelial cells do not. This demonstrates that a computational model of this type has the potential to assist in the discovery of rules of cellular behavior.

Systemic Problems: A perspective on stem cell aging and rejuvenation

This review provides balanced analysis of the advances in systemic regulation of young and old tissue stem cells and suggests strategies for accelerating development of therapies to broadly combat age-related tissue degenerative pathologies. Many highlighted recent reports on systemic tissue rejuvenation combine parabiosis with a “silver bullet” putatively responsible for the positive effects. Attempts to unify these papers reflect the excitement about this experimental approach and add value in reproducing previous work. At the same time, defined molecular approaches, which are “beyond parabiosis” for the rejuvenation of multiple old organs represent progress toward attenuating or even reversing human tissue aging.

A Molecular Clock Infers Heterogeneous Tissue Age Among Patients with Barrett's Esophagus

Biomarkers that drift differentially with age between normal and premalignant tissues, such as Barrett’s esophagus (BE), have the potential to improve the assessment of a patient’s cancer risk by providing quantitative information about how long a patient has lived with the precursor (i.e., dwell time). In the case of BE, which is a metaplastic precursor to esophageal adenocarcinoma (EAC), such biomarkers would be particularly useful because EAC risk may change with BE dwell time and it is generally not known how long a patient has lived with BE when a patient is first diagnosed with this condition. In this study we first describe a statistical analysis of DNA methylation data (both cross-sectional and longitudinal) derived from tissue samples from 50 BE patients to identify and validate a set of 67 CpG dinucleotides in 51 CpG islands that undergo age-related methylomic drift. Next, we describe how this information can be used to estimate a patient’s BE dwell time. We introduce a Bayesian model that incorporates longitudinal methylomic drift rates, patient age, and methylation data from individually paired BE and normal squamous tissue samples to estimate patient-specific BE onset times. Our application of the model to 30 sporadic BE patients’ methylomic profiles first exposes a wide heterogeneity in patient-specific BE onset times. Furthermore, independent application of this method to a cohort of 22 familial BE (FBE) patients reveals significantly earlier mean BE onset times. Our analysis supports the conjecture that differential methylomic drift occurs in BE (relative to normal squamous tissue) and hence allows quantitative estimation of the time that a BE patient has lived with BE.

Barrett’s Esophagus (BE) is a metaplastic precursor to esophageal adenocarcinoma (EAC). When a patient is diagnosed with BE, it is generally not known how long he/she has had this condition because BE is asymptomatic. While the question of how long a premalignant tissue or lesion has been resident in an organ (dwell time) may not be of importance for cases where curative interventions are readily available (such as adenomas in the colon), for BE, curative interventions are either costly or carry patient risks. Knowledge of a precursor’s dwell time may therefore be advantageous in determining the cancer risk due to the stepwise accumulation of critical mutations in the precursor. In this study, we create a molecular clock model that infers patient-specific BE onsets from DNA methylation data. We show that there is considerable variation in the predicted BE onset times which translates, using mathematical modeling of EAC, into large variation in individual EAC risks. We make the case that, notwithstanding other known risk factors such as chronological age, gender, reflux status, etc., knowledge of biological tissue age can provide valuable patient-specific risk information when a patient is first diagnosed with BE.

Aging and computational systems biology

Aging research is undergoing a paradigm shift, which has led to new and innovative methods of exploring this complex phenomenon. The systems biology approach endeavors to understand biological systems in a holistic manner, by taking account of intrinsic interactions, while also attempting to account for the impact of external inputs, such as diet. A key technique employed in systems biology is computational modeling, which involves mathematically describing and simulating the dynamics of biological systems. Although a large number of computational models have been developed in recent years, these models have focused on various discrete components of the aging process, and to date no model has succeeded in completely representing the full scope of aging. Combining existing models or developing new models may help to address this need and in so doing could help achieve an improved understanding of the intrinsic mechanisms which underpin aging.

Systems Medicine: The Future of Medical Genomics, Healthcare, and Wellness

Recent advances in genomics have led to the rapid and relatively inexpensive collection of patient molecular data including multiple types of omics data. The integration of these data with clinical measurements has the potential to impact on our understanding of the molecular basis of disease and on disease management. Systems medicine is an approach to understanding disease through an integration of large patient datasets. It offers the possibility for personalized strategies for healthcare through the development of a new taxonomy of disease. Advanced computing will be an important component in effectively implementing systems medicine. In this chapter we describe three computational challenges associated with systems medicine: disease subtype discovery using integrated datasets, obtaining a mechanistic understanding of disease, and the development of an informatics platform for the mining, analysis, and visualization of data emerging from translational medicine studies.

Integration of 'omics' data in aging research: from biomarkers to systems biology

Age is the strongest risk factor for many diseases including neurodegenerative disorders, coronary heart disease, type 2 diabetes and cancer. Due to increasing life expectancy and low birth rates, the incidence of age-related diseases is increasing in industrialized countries. Therefore, understanding the relationship between diseases and aging and facilitating healthy aging are major goals in medical research. In the last decades, the dimension of biological data has drastically increased with high-throughput technologies now measuring thousands of (epi) genetic, expression and metabolic variables. The most common and so far successful approach to the analysis of these data is the so-called reductionist approach. It consists of separately testing each variable for association with the phenotype of interest such as age or age-related disease. However, a large portion of the observed phenotypic variance remains unexplained and a comprehensive understanding of most complex phenotypes is lacking. Systems biology aims to integrate data from different experiments to gain an understanding of the system as a whole rather than focusing on individual factors. It thus allows deeper insights into the mechanisms of complex traits, which are caused by the joint influence of several, interacting changes in the biological system. In this review, we look at the current progress of applying omics technologies to identify biomarkers of aging. We then survey existing systems biology approaches that allow for an integration of different types of data and highlight the need for further developments in this area to improve epidemiologic investigations.

A systematic review on the role of environmental toxicants in stem cells aging

Stem cells are an important target for environmental toxicants. As they are the main source for replenishing of organs in the body, any changes in their normal function could affect the regenerative potential of organs, leading to the appearance of age-related disease and acceleration of the aging process. Environmental toxicants could exert their adverse effect on stem cell function via multiple cellular and molecular mechanisms, resulting in changes in the stem cell differentiation fate and cell transformation, and reduced self-renewal capacity, as well as induction of stress-induced cellular senescence. The present review focuses on the effect of environmental toxicants on stem cell function associated with the aging process. We categorized environmental toxicants according to their preferred molecular mechanism of action on stem cells, including changes in genomic, epigenomic, and proteomic levels and enhancing oxidative stress. Pesticides, tobacco smoke, radiation and heavy metals are well-studied toxicants that cause stem cell dysfunction via induction of oxidative stress. Transgenerational epigenetic changes are the most important effects of a variety of toxicants on germ cells and embryos that are heritable and could affect health in the next several generations. A better understanding of the underlying mechanisms of toxicant-induced stem cell aging will help us to develop therapeutic intervention strategies against environmental aging. Meanwhile, more efforts are required to find the direct in vivo relationship between adverse effect of environmental toxicants and stem cell aging, leading to organismal aging.

Regenerative orthopaedics: in vitro, in vivo...in silico

In silico, defined in analogy to in vitro and in vivo as those studies that are performed on a computer, is an essential step in problem-solving and product development in classical engineering fields. The use of in silico models is now slowly easing its way into medicine. In silico models are already used in orthopaedics for the planning of complicated surgeries, personalised implant design and the analysis of gait measurements. However, these in silico models often lack the simulation of the response of the biological system over time. In silico models focusing on the response of the biological systems are in full development. This review starts with an introduction into in silico models of orthopaedic processes. Special attention is paid to the classification of models according to their spatiotemporal scale (gene/protein to population) and the information they were built on (data vs hypotheses). Subsequently, the review focuses on the in silico models used in regenerative orthopaedics research. Contributions of in silico models to an enhanced understanding and optimisation of four key elements-cells, carriers, culture and clinics-are illustrated. Finally, a number of challenges are identified, related to the computational aspects but also to the integration of in silico tools into clinical practice.